This invention relates to a noise reduction system for reducing noise contained in a speech signal when the speech signal is analyzed before being transmitted and/or recognized.
Various types of noise reduction systems based on, for example, a method using a close-talking microphone, a spectral subtraction method, a method using a plurality of microphones, and a filtering method have been proposed hitherto. The noise reduction system based on the method using a close-talking microphone utilizes the directivity of the microphone. In the noise reduction system based on the spectral subtraction method, noise only is previously registered, and this registered noise is subtracted from a noise-superposed speech signal. The noise reduction system based on the method using plural microphones utilizes, for example, the phase difference attributable to the different locations of the plural microphones. In the noise reduction system based on the filtering method, a speech signal only is extracted by filtering when the bandwidth of the speech signal differs from that of noise.
On the other hand, a neural network trained on the basis of a mapping of a set of speech waveform inputs containing noise and a set of speech signal outputs freed from noise has been proposed, as described in IEEE Proceedings of ICASSP (International Conference on Acoustics, Speech and Signal Processing) 88, pp. 553-556.
The conventional noise reduction systems described above, based on the method using the close-talking microphone have the problem of feasibility of usage due to the necessity for provision of the close-talking microphone. Also, conventional systems based on the spectral subtraction method and the filtering method are not fully satisfactory in that they are effective only when the characteristics of noise is already known. Further, conventional systems based on the method using the plural microphones have the problem of necessity for determination of suitable locations of the plural microphones required for noise reduction.
On the other hand, the method for reducing noise by the use of the neural network has the problem of degradation of the phonemic intelligibility of a noise-free speech output signal.